Try to rely only ad langgraph

app.py

@@ -64,60 +64,98 @@ class BasicAgent:
         print(f"Agent returning fixed answer: {final_answer}")
         return final_answer, result["messages"]
 
+    # def assistant(self, state: State):
+    #     print("Assistant call state:", state)
+    #     messages = state.get("messages", [])
+        
+    #     # Add system message only once
+    #     if not any(isinstance(m, SystemMessage) for m in messages):
+    #         textual_description_of_tool="""
+    #             search_tool(question: str, max_length: int = 2048) -> str:
+    #                 Search info in the web.
+    #                 Call example:
+                    
+    #                     self.search_tool("Who won the election 2008 in the USA?", max_length = 4096)
+                
+    #                 Args:
+    #                     question: Question string
+    #                     max_length: maximum chars in the output (if exceeded the first "max_length" characters will be taken)
+                
+    #                 Returns:
+    #                     A single string containing the info from the web.
+    
+    #         """
+            
+    #         sys_msg = SystemMessage(
+    #             content=f"""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string. 
+    #             You can use provided tools:\n{textual_description_of_tool}"""
+    #         )
+    #         messages = [sys_msg] + messages
+    
+    #     print("Calling model with tools invoke...")
+    #     new_msg = self.model_with_tools.invoke(messages)
+    #     print("Calling model with tools invoke finished, result:", new_msg)
+
+    #     # Detect tool call
+    #     if "tool_calls" in new_msg.additional_kwargs:
+    #         tool_call = new_msg.additional_kwargs["tool_calls"][0]
+    #         tool_response = self.search_tool(**eval(tool_call["function"]["arguments"]))
+    
+        #     tool_msg = ToolMessage(
+        #         tool_call_id=tool_call["id"],
+        #         content=tool_response,
+        #         name=tool_call["function"]["name"]
+        #     )
+    
+        #     return {
+        #         "question": state["question"],
+        #         "messages": messages + [new_msg, tool_msg],
+        #     }
+    
+        # # new_messages = add_messages(messages, [new_msg])
+        # return {
+        #     "question": state["question"],
+        #     "messages": messages + [new_msg],
+        # }
+
     def assistant(self, state: State):
         print("Assistant call state:", state)
         messages = state.get("messages", [])
-        
+    
         # Add system message only once
         if not any(isinstance(m, SystemMessage) for m in messages):
-            textual_description_of_tool="""
+            textual_description_of_tool = """
                 search_tool(question: str, max_length: int = 2048) -> str:
-                    Search info in the web.
+                    Search info on the web.
                     Call example:
-                    
+    
                         self.search_tool("Who won the election 2008 in the USA?", max_length = 4096)
-                
+    
                     Args:
                         question: Question string
-                        max_length: maximum chars in the output (if exceeded the first "max_length" characters will be taken)
-                
+                        max_length: maximum chars in the output (if exceeded, the first "max_length" characters will be taken)
+    
                     Returns:
                         A single string containing the info from the web.
-    
             """
             
             sys_msg = SystemMessage(
-                content=f"""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string. 
-                You can use provided tools:\n{textual_description_of_tool}"""
+                content=f"""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending on whether the element to be put in the list is a number or a string. 
+    You can use provided tools:\n{textual_description_of_tool}"""
             )
             messages = [sys_msg] + messages
     
         print("Calling model with tools invoke...")
         new_msg = self.model_with_tools.invoke(messages)
         print("Calling model with tools invoke finished, result:", new_msg)
-
-        # Detect tool call
-        if "tool_calls" in new_msg.additional_kwargs:
-            tool_call = new_msg.additional_kwargs["tool_calls"][0]
-            tool_response = self.search_tool(**eval(tool_call["function"]["arguments"]))
-    
-            tool_msg = ToolMessage(
-                tool_call_id=tool_call["id"],
-                content=tool_response,
-                name=tool_call["function"]["name"]
-            )
-    
-            return {
-                "question": state["question"],
-                "messages": messages + [new_msg, tool_msg],
-            }
     
-        # new_messages = add_messages(messages, [new_msg])
+        # Let LangGraph handle tool routing
         return {
             "question": state["question"],
-            "messages": messages + [new_msg],
+            "messages": add_messages(messages, [new_msg]),
         }
 
+
     def search_tool(self, question: str, max_length: int = 2048) -> str:
         """
             Search info in the web.